A review of the use of artificial intelligence methods in infrastructure systems

Engineering Applications of Artificial Intelligence, Journal Year: 2022, Volume and Issue: 116, P. 105472 - 105472

Published: Oct. 18, 2022

The artificial intelligence (AI) revolution offers significant opportunities to capitalise on the growth of digitalisation and has potential enable 'system systems' approach required in increasingly complex infrastructure systems. This paper reviews extent which research economic sectors engaged with fields AI, investigate specific AI methods chosen purposes they have been applied both within across sectors. Machine learning is found dominate this field, such as neural networks, support vector machines, random forests among most popular. automated reasoning technique fuzzy logic also seen widespread use, due its ability incorporate uncertainties input variables. Across energy, water wastewater, transport, telecommunications, main are network provision, forecasting, routing, maintenance security, quality management. data-driven nature flexibility, work conducted a range sizes at different temporal geographic scales. However, there remains lack integration planning policy concerns, stakeholder engagement quantitative feasibility assessment, majority focuses type infrastructure, an absence beyond individual To solutions be implemented into real-world systems, will need move away from siloed perspective adopt more interdisciplinary that considers increasing interconnectedness these

Language: Английский

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A machine learning approach for early warning of cyanobacterial bloom outbreaks in a freshwater reservoir

Journal of Environmental Management, Journal Year: 2021, Volume and Issue: 288, P. 112415 - 112415

Published: March 26, 2021

Language: Английский

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A deep learning method for cyanobacterial harmful algae blooms prediction in Taihu Lake, China

Harmful Algae, Journal Year: 2022, Volume and Issue: 113, P. 102189 - 102189

Published: Jan. 28, 2022

Language: Английский

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From Fully Physical to Virtual Sensing for Water Quality Assessment: A Comprehensive Review of the Relevant State-of-the-Art

Sensors, Journal Year: 2021, Volume and Issue: 21(21), P. 6971 - 6971

Published: Oct. 20, 2021

Rapid urbanization, industrial development, and climate change have resulted in water pollution the quality deterioration of surface groundwater at an alarming rate, deeming its quick, accurate, inexpensive detection imperative. Despite latest developments sensor technologies, real-time determination certain parameters is not easy or uneconomical. In such cases, use data-derived virtual sensors can be effective alternative. this paper, feasibility sensing for assessment reviewed. The review focuses on overview key a particular case development corresponding cost estimates their monitoring. further evaluates current state-of-the-art terms modeling approaches used, studied, whether inputs were pre-processed by interrogating relevant literature published between 2001 2021. identified artificial neural networks, random forest, multiple linear regression as dominant machine learning techniques used developing inferential models. survey also highlights need comprehensive system internet things environment. Thus, formulates specification book advanced process (that involves module) that enable near monitoring quality.

Language: Английский

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Advanced Machine Learning Model for Prediction of Drought Indices using Hybrid SVR-RSM

Water Resources Management, Journal Year: 2022, Volume and Issue: 37(2), P. 683 - 712

Published: Dec. 9, 2022

Language: Английский

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